In this article we described the design and verification of the Pulse Wave Database, and illustrated its utility through a series of case studies. Both the database and the code (described here) used to create and analyse the database are publicly available.
The arterial pulse wave (PW) is a rich source of information on cardiovascular (CV) health. It is widely measured by both consumer and clinical devices. However, the physical determinants of the PW are not yet fully understood, and the development of PW analysis algorithms is limited by a lack of PW datasets containing reference CV measurements. Our aim was to create a database of PWs simulated by a computer to span a range of CV conditions, representative of a sample of healthy adults.
The typical CV properties of 25-75 year olds were identified through a literature review. These were used as inputs to a computational model to simulate PWs for subjects of each age decade. Pressure, flow velocity, luminal area and photoplethysmographic (PPG) PWs were simulated at common measurement sites, and PW indices were extracted.
The database, containing PWs from 4,374 virtual subjects, was verified by comparing the simulated PWs and derived indices with corresponding in vivo data. Good agreement was observed, with well-reproduced age-related changes in haemodynamic parameters and PW morphology. The utility of the database was demonstrated through case studies providing novel haemodynamic insights, in silico assessment of PW algorithms, and pilot data to inform the design of clinical PW algorithm assessments.
In conclusion, the publicly available PW database (DOI: 10.5281/zenodo.2633175) is a valuable resource for understanding CV determinants of PWs, and for the development and pre-clinical assessment of PW analysis algorithms. It is particularly useful because the exact CV properties which generated each PW are known.
Link to full text
Charlton P.H., Mariscal Harana, J., Vennin, S., Li, Y., Chowienczyk, P. & Alastruey, J., “Modelling arterial pulse waves in healthy ageing: a database for in silico evaluation of haemodynamics and pulse wave indices,” AJP Hear. Circ. Physiol., 317(5), pp.H1062-H1085, 2019.
Additional materials related to the article are available at DOI: 10.5281/zenodo.3374476.
Replicating this study
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